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使用人工智能模型预测复发妊娠糖尿病:一项回顾性队列研究
Min Chen1, Weijiao Xu2, Yanni Guo1
1Department of Obstetrics and Gynecology, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, Fuzhou, China.
Archives of gynecology and obstetrics
|July 30, 2024
概括
新型的人工智能 (AI) 模型可以预测怀孕期糖尿病 (GDM) 风险在怀孕早期复发. 这些人工智能工具为及时干预提供了更好的准确性,以及更好的孕产妇和胎儿结果.
科学领域:
- 生殖医学 生殖医学
- 医疗信息学 医疗信息学
- 生物统计学 生物统计学
背景情况:
- 复发性妊娠糖尿病 (GDM) 对母亲和胎儿的健康构成风险.
- 早期识别高风险出现GDM复发的妇女对于及时干预至关重要.
- 使用早期怀孕特征的预测模型可以帮助风险分层.
研究的目的:
- 开发和评估人工智能 (AI) 模型,用于预测怀孕14周之前的复发性GDM.
- 为了比较各种AI算法的性能与GDM复发预测的传统后勤回归.
- 为了确定预测GDM复发的早期怀孕的关键特征.
主要方法:
- 分析了一组588名在先前怀孕中有GDM病史的妇女.
- 最小绝对收缩和选择运算符 (LASSO) 回归被用于特征选择.
- 构建和比较了五种AI模型 (SVM,XGB,LGB,DTC,RF) 和后勤回归.
主要成果:
- 55.4%的女性在随后的怀孕中经历了GDM复发.
- 人工智能模型,特别是LGB,RF和XGB,与后勤回归 (AUROC 0.696) 相比,显示出更好的预测性能 (AUROC 0.942,0.936,0.924).
- 轻度梯度增强 (LGB) 模型显示出卓越的准确性,优异的校准和卓越的净收益.
结论:
- 人工智能模型,特别是LGB,提供了一个非常准确和可靠的方法来预测怀孕早期的复发性GDM风险.
- 这些预测工具可以使医疗保健提供者提供个性化的建议和实施预防策略.
- 早期预测GDM复发可以通过启用主动管理,显著改善母亲和胎儿的福祉.
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